Poisson Count Models to Explain the Adoption of Agricultural and Natural Resource Management Technologies by Small Farmers in Central American Countries

Abstract Evaluations of the factors influencing the adoption of agricultural and natural resource management technologies among small farmers in developing countries have been mostly limited to qualitative discussions or simple descriptive statistics resulting in superficial and inconclusive findings. This study introduces the use of Poisson Count Regressions as a statistically appropriate procedure to analyze certain common types of adoption data. It uses them to assess the impact of key socio-economic, bio-physical, and institutional factors on the adoption of integrated pest management, agroforestry, and soil conservation technologies among small farmers in three Central American countries: Costa Rica, Panama, and El Salvador.